{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorflow version: 2.0.0\n"
     ]
    }
   ],
   "source": [
    "print('Tensorflow version: {}'.format(tf.__version__))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import  matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pathlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dir = 'D:/2_class'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_root = pathlib.Path(data_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "D:\\2_class\\airplane\n",
      "D:\\2_class\\lake\n"
     ]
    }
   ],
   "source": [
    "for item in data_root.iterdir():\n",
    "    print(item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 提取出所有路径的所有对象\n",
    "all_image_path = list(data_root.glob('*/*'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[WindowsPath('D:/2_class/lake/lake_698.jpg'),\n",
       " WindowsPath('D:/2_class/lake/lake_699.jpg'),\n",
       " WindowsPath('D:/2_class/lake/lake_700.jpg')]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_image_path[-3:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#列表推导式转化地址格式\n",
    "all_image_path = [str(path) for path in all_image_path]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 随机打乱顺序\n",
    "random.shuffle(all_image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['D:\\\\2_class\\\\lake\\\\lake_141.jpg', 'D:\\\\2_class\\\\lake\\\\lake_298.jpg']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_image_path[10: 12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1400"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_count = len(all_image_path)\n",
    "image_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取文件夹名生成标签\n",
    "label_names = sorted(item.name for item in data_root.glob('*/'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['airplane', 'lake']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "label_to_index = dict((name, index) for index, name in enumerate(label_names))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'airplane': 0, 'lake': 1}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_to_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 通过上一级目录将图片与标签一一对应\n",
    "all_image_label = [label_to_index[pathlib.Path(p).parent.name] for p in all_image_path]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 0, 0, 1, 0]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_image_label[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 有显示图片等一系列功能\n",
    "import IPython.display as display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "index_to_label = dict((v, k) for k,v in label_to_index.items())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 'airplane', 1: 'lake'}"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index_to_label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "airplane\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "airplane\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lake\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# 随机取出三张图片\n",
    "for n in range(3):\n",
    "    image_index = random.choice(range(len(all_image_path)))\n",
    "    display.display(display.Image(all_image_path[image_index]))\n",
    "    print(index_to_label[all_image_label[image_index]])\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'D:\\\\2_class\\\\airplane\\\\airplane_567.jpg'"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_path = all_image_path[34]\n",
    "image_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取图片并解码\n",
    "img_raw = tf.io.read_file(image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "img_tensor = tf.image.decode_image(img_raw)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TensorShape([256, 256, 3])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_tensor.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 转换数据类型成float32\n",
    "img_tensor = tf.cast(img_tensor, tf.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "img_tensor = img_tensor/255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[1.        , 1.        , 0.9372549 ],\n",
       "        [1.        , 1.        , 0.93333334],\n",
       "        [0.99215686, 0.99607843, 0.9254902 ],\n",
       "        ...,\n",
       "        [0.95686275, 0.9490196 , 0.9019608 ],\n",
       "        [0.9529412 , 0.94509804, 0.8980392 ],\n",
       "        [0.94509804, 0.9372549 , 0.8901961 ]],\n",
       "\n",
       "       [[0.9882353 , 0.99215686, 0.92156863],\n",
       "        [0.9843137 , 0.9882353 , 0.91764706],\n",
       "        [0.9882353 , 0.99215686, 0.92156863],\n",
       "        ...,\n",
       "        [0.95686275, 0.9490196 , 0.9019608 ],\n",
       "        [0.9490196 , 0.9411765 , 0.89411765],\n",
       "        [0.94509804, 0.9372549 , 0.8901961 ]],\n",
       "\n",
       "       [[0.9764706 , 0.9843137 , 0.9019608 ],\n",
       "        [0.9764706 , 0.9843137 , 0.9019608 ],\n",
       "        [0.9843137 , 0.99215686, 0.9098039 ],\n",
       "        ...,\n",
       "        [0.9529412 , 0.94509804, 0.8980392 ],\n",
       "        [0.9490196 , 0.9411765 , 0.89411765],\n",
       "        [0.9411765 , 0.93333334, 0.8862745 ]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0.61960787, 0.5803922 , 0.5411765 ],\n",
       "        [0.6392157 , 0.6       , 0.56078434],\n",
       "        [0.6666667 , 0.627451  , 0.5882353 ],\n",
       "        ...,\n",
       "        [0.57254905, 0.54509807, 0.52156866],\n",
       "        [0.5647059 , 0.5372549 , 0.5137255 ],\n",
       "        [0.5568628 , 0.5294118 , 0.5058824 ]],\n",
       "\n",
       "       [[0.627451  , 0.5764706 , 0.5411765 ],\n",
       "        [0.6431373 , 0.5921569 , 0.5568628 ],\n",
       "        [0.6627451 , 0.6117647 , 0.5764706 ],\n",
       "        ...,\n",
       "        [0.5764706 , 0.54901963, 0.5254902 ],\n",
       "        [0.5647059 , 0.5372549 , 0.5137255 ],\n",
       "        [0.5529412 , 0.5254902 , 0.5019608 ]],\n",
       "\n",
       "       [[0.627451  , 0.5764706 , 0.5411765 ],\n",
       "        [0.6392157 , 0.5882353 , 0.5529412 ],\n",
       "        [0.6509804 , 0.6       , 0.5647059 ],\n",
       "        ...,\n",
       "        [0.5647059 , 0.5372549 , 0.5137255 ],\n",
       "        [0.56078434, 0.53333336, 0.50980395],\n",
       "        [0.54901963, 0.52156866, 0.49803922]]], dtype=float32)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_tensor.numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 预处理函数，channel3表示彩色图片\n",
    "def load_preprosess(path):\n",
    "    img_raw = tf.io.read_file(path)\n",
    "    img_tensor = tf.image.decode_jpeg(img_raw, channels=3)\n",
    "    img_tensor = tf.image.resize(img_tensor, [256, 256])\n",
    "    img_tensor = tf.cast(img_tensor, tf.float32)\n",
    "    img = img_tensor/255\n",
    "    return img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_path = all_image_path[800]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0xe66b6c8>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(load_preprosess(image_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_ds = tf.data.Dataset.from_tensor_slices(all_image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_dataset = path_ds.map(load_preprosess)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 标签不需要经过上述预处理\n",
    "label_dataset = tf.data.Dataset.from_tensor_slices(all_image_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MapDataset shapes: (256, 256, 3), types: tf.float32>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将图片和标签打包成数据集\n",
    "dataset = tf.data.Dataset.zip((image_dataset, label_dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 分割训练集和测试集\n",
    "test_count = int(image_count*0.2)\n",
    "train_count = image_count - test_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1120, 280)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_count, test_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset = dataset.skip(test_count)\n",
    "test_dataset = dataset.take(test_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size = 32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset = train_dataset.shuffle(train_count).batch(batch_size)\n",
    "test_dataset = test_dataset.batch(batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "steps_epoch = train_count//batch_size\n",
    "validation_steps = test_count//batch_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
